The main focus of this paper is to propose high quality, low complexity predictive torque control for IPMSM, which typically exhibits a high level of non-uniformity. Particular solution to this problem may results in high complexity flux mapping, which negatively impacts complexity of the control algorithm. To achieve sufficient accuracy while complexity of the control remain acceptable, we propose to design accurate model which is approximated in a piece-wise manner addressing the most dominant effects on the drive behavior. This is done by state dependent terms using data collected by prior commissioning procedures and verified by FEM simulation. Resulting mathematical model is very simple to implement. We use predictive control with finite control set and cost function following the idea of direct torque control. The proposed controller has been experimentally tested and compared to the controller with conventional mathematical model to demonstrate the effect of the model accuracy on control performance.

This paper deals with the design and real-time implementation of a stator turn fault (STF) indicator for online detection of inter-turn short circuit (ITSC) faults in interior permanent magnet synchronous motor (IPMSM) drives. First an evaluation function is defined based on the average value of the spatial saturation harmonic of the machine over an observation window during the online operation of the drive. Then, based on the value of the load current, a correction factor is set for each condition using a look-up table (LUT) to eliminate the dependency of the saturation saliency on the load current. Finally the STF indicator is obtained by dividing the evaluation function by the correction factor for each load condition. A developped hardware FFT processor is used to extract the saturation saliency from the transient inductance of the machine, estimated online by applying an excitation with voltage pulses using the switching of the inverter and then measuring the resulting current slope. The model is embedded into a field programmable gate array (FPGA) and experimental testing is used to evaluate the performance of the proposed STF indicator on a dedicated designed IPMSM with modified stator windings.

The most common control algorithms for PMSM are based on simplified interpretation of the mathematical model, assuming strictly harmonic signals and linear distribution of the magnetic flux of permanent magnets in the air gap. Nevertheless neglected phenomenons in the mathematical mode leads to deterioration of the torque and overall it may lower the efficiency of the machine. Therefore in order to improve efficiency and torque quality, the aforementioned effects needs to be taken into account, when designing mathematical model, where, stator inductance and magnetic flux of permanent magnets are considered a function of the rotor position. the optimal reference current is no longer projected into d, q coordinated system as a static dc value, which significantly increase the demands on the tuning of cascade structure of PI controllers. An alternative is to use predictive control.In this paper we seek for simple and yet robust control with comparable results as a standard solution based on d, q coordinated system and linear controllers. For this purpose we use simple version of predictive control working with limited control action set (FCS-MPC) with precise model defined in rotating d, q reference frame The resulting algorithm provides high quality torque control performance while taking into account Joule losses in the motor.

Dual-motor single inverter drives reduce installation space, weight and overall costs. On the other hand, complexity of the control increases significantly, since the condition on each electric motor can vary in a wide range. Today, majority of control algorithms are based on field oriented control. The consequences of parallel connection of induction motors are addressed by prioritizing model of the motors with higher relevance to the control. The control problem becomes even more complicated when the drive is equipped with common sensors measuring phase currents at the inverter output only. Performance of the field oriented control strongly depends on the model with full state, which is not available trough measurement, due to the lack of current sensor for particular motors. We propose to simplify the model of dual motor drive and use it with finite control set model predictive control (FCS-MPC). The steady state solution of the control problem is used to improve the control performance. This is achieved as an additional term in the cost function. The algorithm is designed with respect to maximum simplicity and its properties are tested in simulations as well as in a real experiment on the laboratory prototype of a dual induction motor drive of rated power 2×4.5 kW.

Finite control set model predictive control (FCS-MPC) has become very popular form of predictive control among the technical society. Thank to its flexibility and well understood and simple structure, it is well suited for control of ac drives. It represents very interesting alternative for conventional control schemes based on cascade structures with PI controllers. The substantial advantage of MPC based approaches, is the ability of control so called MIMO (Multiple Input Multiple Output) systems in a simple way. This paper deals with the design of FCS-MPC for control of multiple induction machine fed from single inverter. Such drive configuration can offer significant cost and installation space reduction. However the complexity of a control design significantly increases. In multi - motor drives, the condition on each electric machine can vary. Typically, this is a case of traction drives, where the load on each electric machine can vary due to the inhomogeneous friction conditions on the railway track. We propose to use FCS-MPC algorithm as a simple alternative to conventional cascade control approaches. In order to verify the performance of proposed algorithm, we have tested the control technique in simulations and experiments on laboratory prototype of rated power 4.5 kW.

Finite control set model predictive control (FS-MPC) has been shown to be a very effective approach to control of PMSM drives. FS-MPC is a very flexible tool since it can evaluate an arbitrary loss function. However, design of the appropriate loss function for the problem can be a challenge especially when the design input is visible only on the long horizon. An example where this problem becomes apparent is the main propulsion drive of a traction vehicle fed from a dc catenary. Specifically, the catenary voltage is subject to short circuits, fast changes, harmonics and other disturbances which can vary in very wide range. Therefore, the drive is equipped with the trolley-wire input LC filter. The filter is almost undamped by design in order to achieve maximum efficiency and the control strategy needs to secure active damping of the filter to guarantee the drive stability. While it is possible to introduce active damping terms to the loss function, it is hard to predict its properties. In this paper, we consider decomposition of the problem to control of the LC filter and PMSM drive. We show that the resulting controllers can be elegantly combined using Bellman's principle of optimality. The resulting controller is easy to design and its performance is demonstrated in simulation and experiments on 10.7 kW drive.